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Learn how to use in-memory PDF bytes in your knowledge base.
pip install pypdf
from agno.agent import Agent
from agno.knowledge.pdf import PDFBytesKnowledgeBase
from agno.vectordb.lancedb import LanceDb
vector_db = LanceDb(
table_name="recipes_async",
uri="tmp/lancedb",
)
with open("data/pdfs/ThaiRecipes.pdf", "rb") as f:
pdf_bytes = f.read()
knowledge_base = PDFBytesKnowledgeBase(
pdfs=[pdf_bytes],
vector_db=vector_db,
)
knowledge_base.load(recreate=False) # Comment out after first run
agent = Agent(
knowledge=knowledge_base,
search_knowledge=True,
)
agent.print_response("How to make Tom Kha Gai?", markdown=True)
| Parameter | Type | Default | Description |
|---|---|---|---|
| pdfs | Union[List[bytes], List[IO]] | - | List of PDF content as bytes or IO streams. |
| exclude_files | List[str] | [] | List of file patterns to exclude (inherited from base class). |
| reader | Union[PDFReader, PDFImageReader] | PDFReader() | A PDFReader or PDFImageReader that converts the PDFs into Documents for the vector database. |
PDFBytesKnowledgeBase is a subclass of the AgentKnowledge class and has access to the same params.
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